Best Semantic Search Software for Mac

*GraphDB allows you to link diverse data, index it for semantic search and enrich it via text analysis to build big knowledge graphs.* GraphDB is a highly efficient and robust graph database with RDF and SPARQL support. The GraphDB database supports a highly available replication cluster, which has been proven in a number of enterprise use cases that required resilience in data loading and query answering. If you need a quick overview of GraphDB or a download link to its latest releases, please visit the GraphDB product section. GraphDB uses RDF4J as a library, utilizing its APIs for storage and querying, as well as the support for a wide variety of query languages (e.g., SPARQL and SeRQL) and RDF syntaxes (e.g., RDF/XML, N3, Turtle).

Bloomreach personalizes the e-commerce experience. Its data engine unifies real-time customer and product data so businesses understand what customers really want. By connecting that understanding to every channel, the e-commerce experience becomes limitless — reflecting a changing customer as they shop. Amplified by the speed and scale of Loomi, Bloomreach's AI for e-commerce, this creates endless new paths to purchase. Bloomreach products include: Engagement, a marketing automation platform; Discovery, an e-commerce search solution; Content, a headless CMS; and Clarity, AI-powered conversational shopping. The company has multiple AI patents and serves global brands that include Williams-Sonoma, Bosch, Puma, and Marks & Spencer.

Build a natural language interface for your data. NLP is at the core of modern enterprise data processing. We provide developers with the right tools to build production-ready NLP systems quickly and efficiently. Our open-source framework for scalable, API-driven NLP application architectures. We believe in sharing. Our software is open source. We value our community, and we make modern NLP easily accessible, practical, and scalable. Natural language processing (NLP) is a branch of AI that enables machines to process and interpret human language. In general, by implementing NLP, companies can leverage human language to interact with computers and data. Areas of NLP include semantic search, question answering (QA), conversational AI (chatbots), semantic search, text summarization, question generation, text generation, machine translation, text mining, speech recognition, to name a few use cases.